Recovery and analysis of transcriptome subsets from pooled single-cell RNA-seq libraries.

ABSTRACT: Single-cell RNA sequencing (scRNA-seq) methods generate sparse gene expression profiles for thousands of single cells in a single experiment. The information in these profiles is sufficient to classify cell types by distinct expression patterns but the high complexity of scRNA-seq libraries often prevents full characterization of transcriptomes from individual cells. To extract more focused gene expression information from scRNA-seq libraries, we developed a strategy to physically recover the DNA molecules comprising transcriptome subsets, enabling deeper interrogation of the isolated molecules by another round of DNA sequencing. We applied the method in cell-centric and gene-centric modes to isolate cDNA fragments from scRNA-seq libraries. First, we resampled the transcriptomes of rare, s

SUBMITTER: Riemondy KA 

PROVIDER: S-EPMC6393243 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature